The development of some types of automatic speech recognition (ASR) systems or speech recognition applications involves the use of large sets of audio data that conventionally require manual transcription (i.e., transcription by one or more humans). One example of such a speech processing application is one that uses natural language understanding to enable a speech engine to recognize a user's utterance. To ensure that such applications correctly identify an utterance, natural language understanding systems typically are trained using a large corpus of transcribed and classified responses to an open-ended prompt, such as “How may I help you?” An example is a call routing application, which uses statistical-based natural language understanding to direct incoming calls to a particular destination based on information provided by a user. A call routing application may be trained to route calls by providing the application with a large corpus (e.g., 20,000-40,000 samples) of user requests and hand coded results (e.g., desired destinations). Such a large corpus is typically used to ensure that the application learns how to generalize user inputs are that most user inputs are routed properly.
Another type of ASR system that typically employs a large manually transcribed data set is one employing an updatable grammar. Some speech processing applications use one or more grammars to constrain the possible sequences of words recognized by the system. However, grammars written by an application developer for a particular application may not include all of the utterances that a user may say in response to interactions with the system, leading to poor speech recognition. Speech recognition may be improved by extending the grammar to include additional words or phrases that were not included in the original grammar provided by the application developer, but which a user is likely to say. Typically, a large set of actual user responses may be collected and manually transcribed and the manually transcribed responses may be used to update the grammar to include any words or phrases not already in the grammar.